Clustered iconography: A resurrected method for representing multidimensional data

Development of graphical methods for representing data has not kept up with progress in statistical techniques. This article presents a brief history of graphical representations of research findings and makes the case for a revival of methods developed in the early and mid-twentieth century, notably ISOTYPE and Chernoff’s faces. It resurrects and improves a procedure, clustered iconography, which enables the presentation of multidimensional data through which readers engage more effectively with the presentation’s central message by way of an easier understanding of relationships between variables. The proposed technique is especially well adapted to the needs and protocols of open-source research.